q sort

a description about q-sort

1. Assignment on q-sort methodology Submitted to : Submitted by : Dr. Suresh A. Priyanka Upreti Dr. Girish Jha Roll no. 20499 M.Sc. Ag. Economics 1st yr.

2. Contents : What is Q- sort? How does Q- methodology work? Steps involved in Q- methodology Advantages of Q- methodology Limitations of Q- methodology References

3. Q methodology ( q-sort) : Q methodology was first described by the American psychologist William Stephenson in 1935 in the article ‘ correlating persons instead of tests ’ fundamentally and in his major work, ‘ the study of behavior : Q technique and its methodology’ . It is basically a systematic study of participants viewpoints. Q methodology provides a foundation for the systematic study of subjectivity, a person’s viewpoint, opinion, beliefs, attitude and the like. ( Brown 1993 )

4. What do we do in q-sort ?? Typically, in a Q methodological study people are presented with a sample of statements about some topic, called the Q-set . Respondents, called the P-set , are asked to rank-order the statements from their individual point of view, according to some preference, judgment or feeling about them, mostly using a quasi-normal distribution. These individual rankings (or viewpoints) are then subject to factor analysis . It correlates persons instead of tests. By correlating people, Q factor analysis gives information about similarities and differences in viewpoint on a particular subject. Q type analysis is useful when the object is to sort out people into groups based on their simultaneous responses to all the variables.

5. How does q methodology works ? According to Brown, Q methodology involves following steps : Definition of the concourse Development of the Q sample Selection of the P set Q sorting Analysis and interpretation

6. 1. Definition of the concourse : In Q, concourse refers to “the flow of communicability surrounding any topic” in “the ordinary conversation, commentary, and discourse of every day life” Brown (1993). Concourse refers to collection of all the possible statements the respondents can make about the subject at hand. A verbal concourse, to which we will restrict ourselves here, may be obtained in a number of ways: interviewing people; participant observation; popular literature, like media reports, newspapers, magazines, novels; and scientific literature, like papers, essays, and books. Concourse is a raw material for Q.

7. 2. DEVELOPMENT OF THE Q-SET : Next, a subset of statements is drawn from the concourse, to be presented to the participants. This is called the Q set (or Q sample) and often consists of 40 to 50 statements, but less or more statements are certainly also possible . Investigator should select the statements widely different from one another in order to make the Q set broadly representative . Finally, the statements are edited where necessary, randomly assigned a number, and statements and the corresponding number are printed on separate cards – the Q deck – for Q sorting.

8. 3. Selection of the p-set : A Q methodological study requires only a limited number of respondents. All that is required are enough subjects to establish the existence of a factor for purposes of comparing one factor with another. This P set usually is smaller than the Q set . The aim is to have four or five persons defining each anticipated viewpoint, which are often two to four, and rarely more than six. The P set is not random . It is a structured sample of respondents who are theoretically relevant to the problem under consideration; for instance, persons who are expected to have a clear and distinct viewpoint regarding the problem and, in that quality, may define a factor .

9. 4. Q sorting : The Q set is given to the respondent in the form of a pack of randomly numbered cards, each card containing one of the statements from the Q set. The respondent is instructed to rank the statements according to some rule – the condition of instruction , typically the person’s point of view regarding the issue - and is provided with a score sheet and a suggested distribution for the Q sorting task. The score sheet is a continuum ranging from most to most, for instance: with “most disagree” on the one end and “most agree” on the other; 4 and in between a distribution that usually takes the form of a quasi-normal distribution.

10. Score sheet : MOST DISAGREE MOST AGREE

11. Q SORTING… The kurtosis of this distribution depends on the controversiality of the topic: in case the involvement, interest or knowledge of the respondents is expected to be low, the distribution should be steeper in order to leave more room for ambiguity, indecisiveness or error in the middle of the distribution. In case respondents are expected to have strong, or well articulated opinions on the topic at issue, the distribution should be flatter in order to provide more room for strong ( dis )agreement with statements. Usually, respondents are requested to adhere to the distribution provided. The range of the distribution depends on the number of statements and its kurtosis. According to Brown (1980), nowadays most Q sets contain 40 to 50 statements and employ a relatively flattened distribution with a range of -5 to +5.

12. 5. ANALYSIS AND INTERPRETATION : First, the correlation matrix of all Q sorts is calculated. This represents the level of (dis)agreement between the individual sorts . Next, this correlation matrix is subject to factor analysis , with the objective to identify the number of natural groupings of Q sorts by virtue of being similar or dissimilar to one another . A factor loading ( factor variable correlation) is determined for each Q sort, expressing the extent to which each Q sort is associated with each factor. The number of factors in the final set depends on the variability in the Q sorts. It is however recommended to take along more than the number of factors that is anticipated in the next step of the analysis – factor rotation – to preserve as much of the variance as possible. Experience has indicated that ‘ the magic number 7 ’ is generally suitable .

13. Analysis and interpretation… This original set of factors is then rotated to arrive at a final set of factors. By rotating the factors, the investigator examines the opinions from different angles. Each resulting final factor represents a group of individual points of view that are highly correlated with each other and uncorrelated with others. The final step before describing and interpreting the factors is the calculation of factor scores and difference scores. A statement’s factor score is the normalized weighted average statement score (Z-score) of respondents that define that factor. Based on their Z-scores, statements can be attributed to the original quasi-normal distribution, resulting in a composite (or idealized ) Q sort for each factor.

14. Analysis and interpretation… The composite Q sort of a factor represents how a hypothetical respondent with a 100% loading on that factor would have ordered all the statements of the Q-set. When a respondent’s factor loading exceeds a certain limit (usually: p < 0.01), this called a defining variate (or variable ). The difference score is the magnitude of difference between a statement’s score on any two factors that is required for it to be statistically significant. When a statement’s score on two factors exceeds this difference score, it is called a distinguishing (or distinctive) statement . A statement that is not distinguishing between any of the identified factors is called a consensus statement.

15. Analysis and interpretation : Factor scores on a factor’s composite Q sort and difference scores point out the salient statements that deserve special attention in describing and interpreting that factor. Usually, the statements ranked at both extreme ends of the composite sort of a factor, called the characterizing statements , are used to produce a first description of the composite point of view represented by that factor. The distinguishing and the consensus statements can be used to highlight the differences and similarities between factors.

16. Advantages of the q-sort method : Q methodology requires fewer participants, which makes it less expensive. In this, statements are collected from the participants opinion and organized by the participants himself. This provides greater insight into what an individual feels about a topic. It combines both qualitative and quantitative aspects. Because of the forced distribution of Q- sort ratings rater error is controlled. After finishing Q-sorts people can make changes if they disagree.

17. Limitations : Q sorting process is extremely time consuming. Both the methods and instructions need to be explained extensively to participants because they are generally unfamiliar with it. Therefore validity is affected if the participant’s lack of comprehension leads to misinterpretation. Q methodology has also been much criticized because it uses a small sample. REFERENCES : Job van exel (2005) : Q Methodology: a sneak preview Daniel J. Ozer, university of California- the Q sort method and the study of personality development Annette L. Valenta (1997) – Q methodology – definition and application in health care informatics

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